60. n 个骰子的点数【难】
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difficulty: 简单
edit_url: https://github.com/doocs/leetcode/edit/main/lcof/%E9%9D%A2%E8%AF%95%E9%A2%9860.%20n%E4%B8%AA%E9%AA%B0%E5%AD%90%E7%9A%84%E7%82%B9%E6%95%B0/README.md
面试题 60. n 个骰子的点数
题目描述
把n个骰子扔在地上,所有骰子朝上一面的点数之和为s。输入n,打印出s的所有可能的值出现的概率。
你需要用一个浮点数数组返回答案,其中第 i 个元素代表这 n 个骰子所能掷出的点数集合中第 i 小的那个的概率。
示例 1:
输入: 1 输出: [0.16667,0.16667,0.16667,0.16667,0.16667,0.16667]
示例 2:
输入: 2 输出: [0.02778,0.05556,0.08333,0.11111,0.13889,0.16667,0.13889,0.11111,0.08333,0.05556,0.02778]
限制:
1 <= n <= 11
解法
1.题目不太好理解,可以先看这个题:https://www.acwing.com/problem/content/76/
2.促进一点理解的题解:https://leetcode.cn/problems/nge-tou-zi-de-dian-shu-lcof/solutions/637778/jian-zhi-offer-60-n-ge-tou-zi-de-dian-sh-z36d/
方法一:动态规划
我们定义 f [ i ] [ j ] f[i][j] f[i][j] 表示投掷 i i i 个骰子,点数和为 j j j 的方案数。那么我们可以写出状态转移方程:
f [ i ] [ j ] = ∑ k = 1 6 f [ i − 1 ] [ j − k ] f[i][j] = \sum_{k=1}^6 f[i-1][j-k] f[i][j]=k=1∑6f[i−1][j−k]
其中 k k k 表示当前骰子的点数,而 f [ i − 1 ] [ j − k ] f[i-1][j-k] f[i−1][j−k] 表示投掷 i − 1 i-1 i−1 个骰子,点数和为 j − k j-k j−k 的方案数。
初始条件为 f [ 1 ] [ j ] = 1 f[1][j] = 1 f[1][j]=1,表示投掷一个骰子,点数和为 j j j 的方案数为 1 1 1。
最终,我们要求的答案即为 f [ n ] [ j ] 6 n \frac{f[n][j]}{6^n} 6nf[n][j],其中 n n n 为骰子个数,而 j j j 的取值范围为 [ n , 6 n ] [n, 6n] [n,6n]。
时间复杂度 O ( n 2 ) O(n^2) O(n2),空间复杂度 O ( 6 n ) O(6n) O(6n)。其中 n n n 为骰子个数。
Python3
class Solution:def dicesProbability(self, n: int) -> List[float]:f = [[0] * (6 * n + 1) for _ in range(n + 1)] #最大情况:投掷n个骰子,最大和为6nfor j in range(1, 7):f[1][j] = 1 #投掷1个骰子,各个和的方案数都是1for i in range(2, n + 1):for j in range(i, 6 * i + 1): #1)投掷i个筛子,和的范围为[i,6*i]for k in range(1, 7): #2)核心递推:方案数的累加if j - k >= 0:f[i][j] += f[i - 1][j - k]m = pow(6, n) #3)n个骰子的总方案数return [f[n][j] / m for j in range(n, 6 * n + 1)]
Java
class Solution {public double[] dicesProbability(int n) {int[][] f = new int[n + 1][6 * n + 1];for (int j = 1; j <= 6; ++j) {f[1][j] = 1;}for (int i = 2; i <= n; ++i) {for (int j = i; j <= 6 * i; ++j) {for (int k = 1; k <= 6; ++k) {if (j >= k) {f[i][j] += f[i - 1][j - k];}}}}double m = Math.pow(6, n);double[] ans = new double[5 * n + 1];for (int j = n; j <= 6 * n; ++j) {ans[j - n] = f[n][j] / m;}return ans;}
}
C++
class Solution {
public:vector<double> dicesProbability(int n) {int f[n + 1][6 * n + 1];memset(f, 0, sizeof f);for (int j = 1; j <= 6; ++j) {f[1][j] = 1;}for (int i = 2; i <= n; ++i) {for (int j = i; j <= 6 * i; ++j) {for (int k = 1; k <= 6; ++k) {if (j >= k) {f[i][j] += f[i - 1][j - k];}}}}vector<double> ans;double m = pow(6, n);for (int j = n; j <= 6 * n; ++j) {ans.push_back(f[n][j] / m);}return ans;}
};
Go
func dicesProbability(n int) (ans []float64) {f := make([][]int, n+1)for i := range f {f[i] = make([]int, 6*n+1)}for j := 1; j <= 6; j++ {f[1][j] = 1}for i := 2; i <= n; i++ {for j := i; j <= 6*i; j++ {for k := 1; k <= 6; k++ {if j >= k {f[i][j] += f[i-1][j-k]}}}}m := math.Pow(6, float64(n))for j := n; j <= 6*n; j++ {ans = append(ans, float64(f[n][j])/m)}return
}
JavaScript
/*** @param {number} n* @return {number[]}*/
var dicesProbability = function (n) {const f = Array.from({ length: n + 1 }, () => Array(6 * n + 1).fill(0));for (let j = 1; j <= 6; ++j) {f[1][j] = 1;}for (let i = 2; i <= n; ++i) {for (let j = i; j <= 6 * i; ++j) {for (let k = 1; k <= 6; ++k) {if (j >= k) {f[i][j] += f[i - 1][j - k];}}}}const ans = [];const m = Math.pow(6, n);for (let j = n; j <= 6 * n; ++j) {ans.push(f[n][j] / m);}return ans;
};
C#
public class Solution {public double[] DicesProbability(int n) {int[,] f = new int[n + 1, 6 * n + 1];for (int j = 1; j <= 6; ++j) {f[1, j] = 1;}for (int i = 2; i <= n; ++i) {for (int j = i; j <= 6 * i; ++j) {for (int k = 1; k <= 6; ++k) {if (j >= k) {f[i, j] += f[i - 1, j - k];}}}}double m = Math.Pow(6, n);double[] ans = new double[5 * n + 1];for (int j = n; j <= 6 * n; ++j) {ans[j - n] = f[n, j] / m;}return ans;}
}
Swift
class Solution {func dicesProbability(_ n: Int) -> [Double] {var f = Array(repeating: Array(repeating: 0, count: 6 * n + 1), count: n + 1)for j in 1...6 {f[1][j] = 1}if n > 1 {for i in 2...n {for j in i...(6 * i) {for k in 1...6 {if j >= k {f[i][j] += f[i - 1][j - k]}}}}}var m = 1.0for _ in 0..<n {m *= 6.0}var ans = Array(repeating: 0.0, count: 5 * n + 1)for j in n...(6 * n) {ans[j - n] = Double(f[n][j]) / m}return ans}
}
方法二:动态规划(空间优化)
我们可以发现,上述方法中的 f [ i ] [ j ] f[i][j] f[i][j] 的值仅与 f [ i − 1 ] [ j − k ] f[i-1][j-k] f[i−1][j−k] 有关,因此我们可以使用滚动数组的方式,将空间复杂度优化至 O ( 6 n ) O(6n) O(6n)。
Python3
class Solution:def dicesProbability(self, n: int) -> List[float]:f = [0] + [1] * 6for i in range(2, n + 1):g = [0] * (6 * i + 1)for j in range(i, 6 * i + 1):for k in range(1, 7):if 0 <= j - k < len(f):g[j] += f[j - k] #仅仅与投掷n-1个骰子的方案数 数组有关f = gm = pow(6, n)return [f[j] / m for j in range(n, 6 * n + 1)]
Java
class Solution {public double[] dicesProbability(int n) {int[] f = new int[7];Arrays.fill(f, 1);f[0] = 0;for (int i = 2; i <= n; ++i) {int[] g = new int[6 * i + 1];for (int j = i; j <= 6 * i; ++j) {for (int k = 1; k <= 6; ++k) {if (j - k >= 0 && j - k < f.length) {g[j] += f[j - k];}}}f = g;}double m = Math.pow(6, n);double[] ans = new double[5 * n + 1];for (int j = n; j <= 6 * n; ++j) {ans[j - n] = f[j] / m;}return ans;}
}
Go
func dicesProbability(n int) (ans []float64) {f := make([]int, 7)for i := 1; i <= 6; i++ {f[i] = 1}for i := 2; i <= n; i++ {g := make([]int, 6*i+1)for j := i; j <= 6*i; j++ {for k := 1; k <= 6; k++ {if j-k >= 0 && j-k < len(f) {g[j] += f[j-k]}}}f = g}m := math.Pow(6, float64(n))for j := n; j <= 6*n; j++ {ans = append(ans, float64(f[j])/m)}return
}
JavaScript
/*** @param {number} num* @return {number[]}*/
var dicesProbability = function (n) {let f = Array(7).fill(1);f[0] = 0;for (let i = 2; i <= n; ++i) {let g = Array(6 * i + 1).fill(0);for (let j = i; j <= 6 * i; ++j) {for (let k = 1; k <= 6; ++k) {if (j - k >= 0 && j - k < f.length) {g[j] += f[j - k];}}}f = g;}const ans = [];const m = Math.pow(6, n);for (let j = n; j <= 6 * n; ++j) {ans.push(f[j] / m);}return ans;
};
C#
public class Solution {public double[] DicesProbability(int n) {int[] f = new int[7];for (int i = 1; i <= 6; ++i) {f[i] = 1;}f[0] = 0;for (int i = 2; i <= n; ++i) {int[] g = new int[6 * i + 1];for (int j = i; j <= 6 * i; ++j) {for (int k = 1; k <= 6; ++k) {if (j - k >= 0 && j - k < f.Length) {g[j] += f[j - k];}}}f = g;}double m = Math.Pow(6, n);double[] ans = new double[5 * n + 1];for (int j = n; j <= 6 * n; ++j) {ans[j - n] = f[j] / m;}return ans;}
}